Abstract
Swarm Robotics are widely conceived as the development of new computationally efficient tools and techniques aimed at easing and enhancing the coordination of multiple robots towards collaboratively accomplishing a certain mission or task. Among the different criteria under which the performance of Swarm Robotics can be gauged, energy efficiency and battery lifetime have played a major role in the literature. However, technological advances favoring power transfer among robots have unleashed new paradigms related to the optimization of the battery consumption considering it as a resource shared by the entire swarm. This work focuses on this context by elaborating on a routing problem for collaborative exploration in Swarm Robotics, where a subset of robots is equipped with battery recharging functionalities. Formulated as a bi-objective optimization problem, the quality of routes is measured in terms of the Pareto trade-off between the predicted area explored by robots and the risk of battery outage in the swarm. To efficiently balance these conflicting two objectives, a bio-inspired evolutionary solver is adopted and put to practice over a realistic experimental setup implemented in the VREP simulation framework. Obtained results elucidate the practicability of the proposed scheme, and suggest future research leveraging power transfer capabilities over the swarm.
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Videos showing how robots move over this scenario can be found at: https://youtu.be/r31teMtWRF0 and https://youtu.be/zewRVZQpvP8.
References
Beni, G.: From swarm intelligence to swarm robotics. In: International Workshop on Swarm Robotics, pp. 1–9 (2004)
Brambilla, M., Ferrante, E., Birattari, M., Dorigo, M.: Swarm robotics: a review from the swarm engineering perspective. Swarm Intell. 7(1), 1–41 (2013)
Miranda, K., Molinaro, A., Razafindralambo, T.: A survey on rapidly deployable solutions for post-disaster networks. IEEE Commun. Mag. 54(4), 117–123 (2016)
Bogue, R., Bogue, R.: Underwater robots: a review of technologies and applications. Ind. Robot: Int. J. 42(3), 186–191 (2015)
Mei, Y., Lu, Y.H., Hu, Y.C., Lee, C.G.: Energy-efficient motion planning for mobile robots. In: IEEE International Conference on Robotics and Automation (ICRA 2004), vol. 5, pp. 4344–4349 (2004)
Johnson, J., Stoops, M., Schwartz, B., Masters, N., Hasan, S.: Techniques for mobile device charging using robotic devices, 15 November 2016. US Patent 9,492,922
Couture-Beil, A., Vaughan, R.T.: Adaptive mobile charging stations for multi-robot systems. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1363–1368 (2009)
Haek, M., Ismail, A.R., Basalib, A., Makarim, N.: Exploring energy charging problem in swarm robotic systems using foraging simulation. Jurnal Teknologi 76(1), 239–244 (2015)
Melhuish, C., Kubo, M.: Collective energy distribution: maintaining the energy balance in distributed autonomous robots using trophallaxis. Distrib. Auton. Robot. Syst. 6, 275–284 (2007)
Schmickl, T., Crailsheim, K.: Trophallaxis among swarm-robots: a biologically inspired strategy for swarm robotics. In: IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, pp. 377–382 (2006)
Schioler, H., Ngo, T.D.: Trophallaxis in robotic swarms-beyond energy autonomy. In: IEEE International Conference on Control, Automation, Robotics and Vision, pp. 1526–1533 (2008)
Schmickl, T., Crailsheim, K.: Trophallaxis within a robotic swarm: bio-inspired communication among robots in a swarm. Auton. Robots 25(1), 171–188 (2008)
Mostaghim, S., Steup, C., Witt, F.: Energy aware particle swarm optimization as search mechanism for aerial micro-robots. In: IEEE Symposium Series on Computational Intelligence, pp. 1–7 (2016)
Lee, J.H., Ahn, C.W., An, J.: A honey bee swarm-inspired cooperation algorithm for foraging swarm robots: an empirical analysis. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 489–493 (2013)
Al Haek, M., Ismail, A.R., Nordin, A., Sulaiman, S., Lau, H.: Modelling immune systems responses for the development of energy sharing strategies for swarm robotic systems. In: International Conference on Computational Science and Technology, pp. 1–6 (2014)
Al Haek, M., Ismail, A.R.: Simulating the immune inspired energy charging mechanism for swarm robotic systems. J. Theor. Appl. Inf. Technol. 95(20), 5473–5483 (2017)
Timmis, J., Ismail, A.R., Bjerknes, J.D., Winfield, A.F.: An immune-inspired swarm aggregation algorithm for self-healing swarm robotic systems. Biosystems 146, 60–76 (2016)
Ismail, A.R., Desia, R., Zuhri, M.F.R.: The initial investigation of the design and energy sharing algorithm using two-ways communication mechanism for swarm robotic systems. In: Phon-Amnuaisuk, S., Au, T.W. (eds.) Computational Intelligence in Information Systems. AISC, vol. 331, pp. 61–71. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-13153-5_7
Wang, J., Liang, Z., Zhang, Z.: Energy-encrypted contactless charging for swarm robots. In: International Magnetics Conference, p. 1 (2017)
He, L., Cheng, P., Gu, Y., Pan, J., Zhu, T., Liu, C.: Mobile-to-mobile energy replenishment in mission-critical robotic sensor networks. In: IEEE INFOCOM, pp. 1195–1203 (2014)
Arvin, F., Samsudin, K., Ramli, A.R.: Swarm robots long term autonomy using moveable charger. In: International Conference on Future Computer and Communication, pp. 127–130 (2009)
Rohmer, E., Singh, S.P., Freese, M.: V-REP: a versatile and scalable robot simulation framework. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1321–1326 (2013)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)
Acknowledgments
E. Osaba and J. Del Ser would like to thank the Basque Government for its funding support through the EMAITEK program. Likewise, the involvement of A. Galvez and A. Iglesias in this work has been funded by the Agencia Estatal de Investigación (grant no. TIN2017-89275-R), the European Union through FEDER Funds (AEI/FEDER), and the project #JU12, jointly supported by the public body SODERCAN and European Funds FEDER (SODERCAN/FEDER).
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Carrillo, M. et al. (2018). A Bio-inspired Approach for Collaborative Exploration with Mobile Battery Recharging in Swarm Robotics. In: Korošec, P., Melab, N., Talbi, EG. (eds) Bioinspired Optimization Methods and Their Applications. BIOMA 2018. Lecture Notes in Computer Science(), vol 10835. Springer, Cham. https://doi.org/10.1007/978-3-319-91641-5_7
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DOI: https://doi.org/10.1007/978-3-319-91641-5_7
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